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Related Experiment Videos

Tileable BTF.

Man-Kang Leung1, Wai-Man Pang, Chi-Wing Fu

  • 1Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong. cskang@ust.hk

IEEE Transactions on Visualization and Computer Graphics
|July 12, 2007
PubMed
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This study introduces a modular framework for applying bidirectional texture functions (BTF) to surfaces. This approach enables efficient, seamless texturing of diverse objects without re-synthesis, decoupling appearance from geometry.

Area of Science:

  • Computer Graphics
  • Material Appearance Modeling

Background:

  • Bidirectional Texture Functions (BTF) capture complex surface appearance under varying lighting and viewing conditions.
  • Applying BTFs efficiently to diverse 3D objects remains a significant challenge in computer graphics.

Purpose of the Study:

  • To present a novel modular framework for efficient BTF application.
  • To enable seamless texturing of various objects using a single set of BTF tiles.
  • To decouple surface appearance from object geometry for greater flexibility.

Main Methods:

  • Developed a framework based on modular BTF tiles as basic building blocks.
  • Introduced a novel synthesis method for high-dimensional, seamless BTF tiles by optimizing sampling strategies.
  • Implemented tile synthesis in a compressed domain to manage large datasets and facilitate GPU storage.

Related Experiment Videos

Main Results:

  • Demonstrated the ability to texture a wide variety of objects seamlessly with a single set of BTF tiles.
  • Achieved efficient decoupling of surface appearance from geometry.
  • Successfully synthesized high-dimensional BTF tiles that are challenging for existing methods.

Conclusions:

  • The proposed framework offers an efficient and flexible solution for applying BTFs.
  • Appearance-geometry decoupling allows for rapid rendering of objects under varied conditions.
  • Compressed domain synthesis enables handling large BTF data and efficient GPU memory usage.